32 citations · 128 across the 27 of their papers we have counts for
9 papers · 1 filter
MobileMamba: Lightweight Multi-Receptive Visual Mamba Network
Haoyang He, Jiangning Zhang, Yuxuan Cai +7
Previous research on lightweight models has primarily focused on CNNs and Transformer-based designs. CNNs, with their local receptive fields, struggle to capture long-range depende…
LLaVA-KD: A Framework of Distilling Multimodal Large Language Models
Yuxuan Cai, Jiangning Zhang, Haoyang He +7
The success of Large Language Models (LLMs) has inspired the development of Multimodal Large Language Models (MLLMs) for unified understanding of vision and language. However, the…
LLaVA-VSD: Large Language-and-Vision Assistant for Visual Spatial Description
Yizhang Jin, Jian Li, Jiangning Zhang +7
Visual Spatial Description (VSD) aims to generate texts that describe the spatial relationships between objects within images. Traditional visual spatial relationship classificatio…
PSPU: Enhanced Positive and Unlabeled Learning by Leveraging Pseudo Supervision
Chengjie Wang, Chengming Xu, Zhenye Gan +3
Positive and Unlabeled (PU) learning, a binary classification model trained with only positive and unlabeled data, generally suffers from overfitted risk estimation due to inconsis…
A Comprehensive Library for Benchmarking Multi-class Visual Anomaly Detection
Jiangning Zhang, Haoyang He, Zhenye Gan +7
Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as indust…
Efficient Multimodal Large Language Models: A Survey
Yizhang Jin, Jian Li, Yexin Liu +10
In the past year, Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in tasks such as visual question answering, visual understanding and reasoning.…
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Haoyang He, Yuhu Bai, Jiangning Zhang +7
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers ar…
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection
Chengjie Wang, Wenbing Zhu, Bin-Bin Gao +6
Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid development. However, the recent development of IAD approach has encountered certain dif…
DMAD: Dual Memory Bank for Real-World Anomaly Detection
Jianlong Hu, Xu Chen, Zhenye Gan +7
Training a unified model is considered to be more suitable for practical industrial anomaly detection scenarios due to its generalization ability and storage efficiency. However, t…